Triple
T38518089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chula Uni |
E922392
|
entity |
| Predicate | refersToFocus |
P198781
|
FINISHED |
| Object | research university |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: research university | Statement: [Chula Uni, refersToFocus, research university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToFocus Context triple: [Chula Uni, refersToFocus, research university]
-
A.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
D.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
E.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ea5f5588190bd0b28c82e975640 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff0491409c8190be40f633a58da0b1 |
completed | May 9, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69ff040bb5cc81909534c7eee85d5e90 |
completed | May 9, 2026, 9:53 a.m. |
| PDg | Predicate description generation | batch_69ff04901ab081908b68563836fcdc99 |
completed | May 9, 2026, 9:55 a.m. |
Created at: May 3, 2026, 4:32 p.m.